Near-optimal coverage trajectories for image mosaicing
using a mini quad-rotor over irregular-shaped ﬁelds
Jaime Del Cerro
ngel de Frutos
Published online: 19 October 2012
Ó Springer Science+Business Media New York 2012
Abstract Aerial images are useful tools for farmers who practise precision agriculture.
The difﬁculty in taking geo-referenced high-resolution aerial images in a narrow time
window considering weather restrictions and the high cost of commercial services are the
main drawbacks of these techniques. In this paper, a useful tool to obtain aerial images by
using low cost unmanned aerial vehicles (UAV) is presented. The proposed system allows
farmers to easily deﬁne and execute an aerial image coverage mission by using geographic
information system tools in order to obtain mosaics made of high-resolution images. The
system computes a complete path for the UAV by taking into account the on-board camera
features once the image requirements and area to be covered are deﬁned. This work
introduces a full four-step procedure: mission deﬁnition, automatic path planning, mission
execution and mosaic generation.
Keywords Aerial images Á Mosaicing Á Coverage path planning Á Aerial robots Á
Mission planner Á Remote sensing
High availability aerial vehicles equipped with inexpensive and lightweight sensors have
become suitable remote sensing (RS) tools, overcoming the deﬁciencies of other RS
options, such as satellites or airplanes. Nowadays, they are able to provide an affordable,
adaptable and fast data acquisition tool for agricultural purposes.
Currently, aerial vehicles (mainly planes) are employed in agriculture for crop obser-
vation and map generation through imaging surveys (Johnson et al. 2003; Herwitz et al.
2004). The maps are usually built by stitching a set of geo-referenced images (e.g.
orthophotos) through mosaicing procedures. These maps give detailed information about
biophysical parameters of the crop ﬁeld. The agricultural experiments reported with aerial
vehicles mainly use waypoint-based navigation features (Johnson et al. 2003; Berni et al.
J. Valente (&) Á D. Sanz Á J. Del Cerro Á A. Barrientos Á M. A
. de Frutos
Centre for Automation and Robotics (UPM-CSIC), c/Jose
rrez Abascal, 2, 28006 Madrid, Spain
Precision Agric (2013) 14:115–132